Uses of Interface
ec.util.RandomChoiceChooserD

Packages that use RandomChoiceChooserD

Package	Description
ec
ec.app.tutorial2
ec.app.tutorial3
ec.breed
ec.es
ec.gp
ec.gp.breed
ec.gp.build
ec.gp.ge.breed
ec.gp.koza
ec.multiobjective.spea2
ec.parsimony
ec.rule.breed
ec.select
ec.spatial
ec.util
ec.vector.breed

Uses of RandomChoiceChooserD in ec

Classes in ec that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	BreedingPipeline A BreedingPipeline is a BreedingSource which provides "fresh" individuals which can be used to fill a new population.
class	BreedingSource A BreedingSource is a Prototype which provides Individuals to populate new populations based on old ones.
class	SelectionMethod A SelectionMethod is a BreedingSource which provides direct IMMUTABLE pointers to original individuals in an old population, not fresh mutable copies.

Uses of RandomChoiceChooserD in ec.app.tutorial2

Classes in ec.app.tutorial2 that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	OurMutatorPipeline OurMutatorPipeline is a BreedingPipeline which negates the sign of genes.

Uses of RandomChoiceChooserD in ec.app.tutorial3

Classes in ec.app.tutorial3 that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	OurSelection

Uses of RandomChoiceChooserD in ec.breed

Classes in ec.breed that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	BufferedBreedingPipeline If empty, a BufferedBreedingPipeline makes a request of exactly num-inds individuals from a single child source; it then uses these individuals to fill requests (returning min each time), until the buffer is emptied, at which time it grabs exactly num-inds more individuals, and so on.
class	CheckingPipeline CheckingPipeline is a BreedingPipeline which just passes through the individuals it receives from its source 0, but only if those individuals ALL pass a validation check (the method allValid(), which you must override).
class	ForceBreedingPipeline ForceBreedingPipeline has one source.
class	GenerationSwitchPipeline GenerationSwitchPipeline is a simple BreedingPipeline which switches its source depending on the generation.
class	InitializationPipeline InitializationPipeline is a BreedingPipeline which simply generates a new random inidividual.
class	MultiBreedingPipeline MultiBreedingPipeline is a BreedingPipeline stores some n child sources; each time it must produce an individual or two, it picks one of these sources at random and has it do the production.
class	ReproductionPipeline ReproductionPipeline is a BreedingPipeline which simply makes a copy of the individuals it recieves from its source.

Uses of RandomChoiceChooserD in ec.es

Classes in ec.es that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	ESSelection ESSelection is a special SelectionMethod designed to be used with evolutionary strategies-type breeders.

Uses of RandomChoiceChooserD in ec.gp

Classes in ec.gp that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	GPBreedingPipeline A GPBreedingPipeline is a BreedingPipeline which produces only members of some subclass of GPSpecies.

Uses of RandomChoiceChooserD in ec.gp.breed

Classes in ec.gp.breed that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	InternalCrossoverPipeline InternalCrossoverPipeline picks two subtrees from somewhere within an individual, and crosses them over.
class	MutateAllNodesPipeline MutateAllNodesPipeline implements the AllNodes mutation algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98.
class	MutateDemotePipeline MutateDemotePipeline works very similarly to the DemoteNode algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98, and is also similar to the "insertion" operator found in Una-May O'Reilly's thesis, "An Analysis of Genetic Programming".
class	MutateERCPipeline MutateERCPipeline works very similarly to the "Gaussian" algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98.
class	MutateOneNodePipeline MutateOneNodesPipeline implements the OneNode mutation algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98.
class	MutatePromotePipeline MutatePromotePipeline works very similarly to the PromoteNode algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98, and is also similar to the "deletion" operator found in Una-May O'Reilly's thesis, "An Analysis of Genetic Programming".
class	MutateSwapPipeline MutateSwapPipeline works very similarly to the Swap algorithm described in Kumar Chellapilla, "A Preliminary Investigation into Evolving Modular Programs without Subtree Crossover", GP98.
class	RehangPipeline RehangPipeline picks a nonterminal node other than the root and "rehangs" it as a new root.
class	SizeFairCrossoverPipeline SizeFairCrossover works similarly to one written in the paper "Size Fair and Homologous Tree Genetic Programming Crossovers" by Langdon (1998).

Uses of RandomChoiceChooserD in ec.gp.build

Classes in ec.gp.build that implement RandomChoiceChooserD

Modifier and Type	Class and Description
(package private) class	UniformGPNodeStorage

Uses of RandomChoiceChooserD in ec.gp.ge.breed

Classes in ec.gp.ge.breed that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	GECrossoverPipeline GECrossoverPipeline is just like ListCrossoverPipeline, except that it will additionally check to verify that the first crossover point is within the range of consumed genes in each parent.
class	GETruncationPipeline GETruncationPipeline removes the unused genes from the end of the vector.

Uses of RandomChoiceChooserD in ec.gp.koza

Classes in ec.gp.koza that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	CrossoverPipeline CrossoverPipeline is a GPBreedingPipeline which performs a strongly-typed version of Koza-style "Subtree Crossover".
class	MutationPipeline MutationPipeline is a GPBreedingPipeline which implements a strongly-typed version of the "Point Mutation" operator as described in Koza I.

Uses of RandomChoiceChooserD in ec.multiobjective.spea2

Classes in ec.multiobjective.spea2 that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	SPEA2TournamentSelection This is a special version of TournamentSelection which restricts the selection to only the archive region (the top 'archiveSize' elements in the subpopulation).

Uses of RandomChoiceChooserD in ec.parsimony

Classes in ec.parsimony that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	BucketTournamentSelection Does a tournament selection, limited to the subpopulation it's working in at the time.
class	DoubleTournamentSelection
class	LexicographicTournamentSelection Does a simple tournament selection, limited to the subpopulation it's working in at the time.
class	ProportionalTournamentSelection This selection method adds parsimony pressure to the regular tournament selection.
class	RatioBucketTournamentSelection Does a tournament selection, limited to the subpopulation it's working in at the time.

Uses of RandomChoiceChooserD in ec.rule.breed

Classes in ec.rule.breed that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	RuleCrossoverPipeline RuleCrossoverPipeline is a BreedingPipeline which implements a simple default crossover for RuleIndividuals.
class	RuleMutationPipeline RuleMutationPipeline is a BreedingPipeline which implements a simple default Mutation for RuleIndividuals.

Uses of RandomChoiceChooserD in ec.select

Classes in ec.select that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	BestSelection Performs a tournament selection restricted to only the best, or worst, n indivdiuals in the population.
class	BoltzmannSelection Similar to FitProportionateSelection, but with a Simulated Annealing style twist.
class	FirstSelection Always picks the first individual in the subpopulation.
class	FitProportionateSelection Picks individuals in a population in direct proportion to their fitnesses as returned by their fitness() methods.
class	GreedyOverselection GreedyOverselection is a SelectionMethod which implements Koza-style fitness-proportionate greedy overselection.
class	MultiSelection MultiSelection is a SelectionMethod which stores some n subordinate SelectionMethods.
class	RandomSelection Picks a random individual in the subpopulation.
class	SigmaScalingSelection Similar to FitProportionateSelection, but with adjustments to scale up/exaggerate differences in fitness for selection when true fitness values are very close to eachother across the population.
class	SUSSelection Picks individuals in a population using the Stochastic Universal Selection (SUS) process, using fitnesses as returned by their fitness() methods.
class	TournamentSelection Does a simple tournament selection, limited to the subpopulation it's working in at the time.

Uses of RandomChoiceChooserD in ec.spatial

Classes in ec.spatial that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	SpatialTournamentSelection A slight modification of the tournament selection procedure for use with spatially-embedded EAs.

Uses of RandomChoiceChooserD in ec.util

Methods in ec.util with parameters of type RandomChoiceChooserD

Modifier and Type	Method and Description
private static int	RandomChoice.exemptZeroes(Object[] objs, RandomChoiceChooserD chooser, int index)
static void	RandomChoice.organizeDistribution(Object[] objs, RandomChoiceChooserD chooser) Same as organizeDistribution(objs, chooser, false);
static void	RandomChoice.organizeDistribution(Object[] objs, RandomChoiceChooserD chooser, boolean allowAllZeros) Normalizes the probabilities associated with an array of objects, then converts them into continuing sums.
static int	RandomChoice.pickFromDistribution(Object[] objs, RandomChoiceChooserD chooser, double prob) Picks a random item from an array of objects, each with an associated probability that is accessed by taking an object and passing it to chooser.getProbability(obj).
static int	RandomChoice.pickFromDistribution(Object[] objs, RandomChoiceChooserD chooser, double prob, int checkboundary) Deprecated.

Uses of RandomChoiceChooserD in ec.vector.breed

Classes in ec.vector.breed that implement RandomChoiceChooserD

Modifier and Type	Class and Description
class	GeneDuplicationPipeline GeneDuplicationPipeline is designed to duplicate a sequence of genes from the chromosome and append them to the end of the chromosome.
class	ListCrossoverPipeline ListCrossoverPipeline is a crossover pipeline for vector individuals whose length may be lengthened or shortened.
class	MultipleVectorCrossoverPipeline MultipleVectorCrossoverPipeline is a BreedingPipeline which implements a uniform (any point) crossover between multiple vectors.
class	VectorCrossoverPipeline VectorCrossoverPipeline is a BreedingPipeline which implements a simple default crossover for VectorIndividuals.
class	VectorMutationPipeline VectorMutationPipeline is a BreedingPipeline which implements a simple default Mutation for VectorIndividuals.